This workflow creates an AI-powered chatbot that interacts with a PostgreSQL database, enabling users to ask questions and retrieve data dynamically. The process begins with a webhook trigger that listens for chat messages. These messages are passed to an AI agent, which uses OpenAI’s GPT-4 model to understand user queries and generate SQL commands. The workflow includes steps to fetch database schema and table details, allowing the AI to craft precise queries. Once a SQL query is generated, it is executed directly against the PostgreSQL database, retrieving the relevant data. This setup is ideal for creating interactive data assistants in business intelligence, analytics, or customer support scenarios, making database information accessible through natural language.
The workflow features key nodes:
– A webhook trigger to start the conversation.
– An AI agent configured with system prompts to interpret user requests and generate SQL commands.
– Additional nodes to extract database schema information and table definitions, aiding in precise query formation.
– An SQL execution node that runs the generated queries against the database.
– OpenAI’s chat model to facilitate natural language processing.
Practical use cases include enabling non-technical users to ask complex data questions, creating interactive dashboards, or automating data retrieval for reports and decision-making.
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